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Updated: Aug 7, 2026
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Diagnosis of Neoplasia in Barrett’s Esophagus using Vital-dye Enhanced Fluorescence Imaging
Published on: May 11, 2014
Complex structural rearrangements are present in high-grade dysplastic Barrett's oesophagus samples
Felicity Newell1, Kalpana Patel2, Michael Gartside2
1QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, Brisbane, QLD, 4006, Australia.
BMC Medical Genomics
|February 6, 2019
Summary
Genomic analysis of Barrett's oesophagus (BE) reveals non-progressors have fewer mutations than those who develop oesophageal adenocarcinoma (EAC). Complex rearrangements in dysplastic BE suggest a role in cancer progression.
Area of Science:
- Genomics
- Cancer Biology
- Gastroenterology
Background:
- Oesophageal adenocarcinoma (EAC) incidence is rising with poor survival rates.
- Barrett's oesophagus (BE) is a precursor to EAC, but most BE cases do not progress to cancer.
- Understanding genomic features of BE and EAC is crucial for identifying at-risk individuals.
Purpose of the Study:
- To assess the genomic features of BE and EAC.
- To compare genomic profiles of non-dysplastic and dysplastic BE with EAC.
- To identify genomic differences between BE that progresses and does not progress to EAC.
Main Methods:
- Whole-genome sequencing of 16 BE samples (non-dysplastic and dysplastic).
- Comparison of BE genome profiles with 22 EAC samples.
- Analysis of somatic variations, mutational signatures, and rearrangement signatures.
Main Results:
- Non-progressor BE samples showed significantly lower somatic variations than dysplastic and other non-dysplastic BE samples.
- EAC samples exhibited the highest levels of somatic genomic variations.
- Mutational signature 17 and localized complex rearrangements were found in dysplastic BE and EAC, but not in non-progressors.
Conclusions:
- Localized complex rearrangements in dysplastic BE samples warrant further investigation.
- Genomic differences highlight potential markers for BE progression to EAC.
- Identifying genomic drivers may aid in early detection and risk stratification for EAC.
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